Daisuke Sakamoto

3.6k citations
168 papers · 2.8k · h-index 29

Impact in

Papers in

Daisuke Sakamoto

150 papers receiving 2.7k citations

Peers

Daisuke Sakamoto
Comparison fields: 5 of 148
  • Human-Computer Interaction 798
  • Social Psychology 858
  • Computer Vision and Pattern Recognition 629
  • Cognitive Neuroscience 369
  • Control and Systems Engineering 435
Replace Naoyuki Kubota with:
Naoyuki Kubota Japan
James F. Cremer United States
Guillem Alenyà Spain
Hugo Jair Escalante Mexico
Alan C. Schultz United States
Gerhard Sagerer Germany
Ronald Poppe Netherlands
Miguel Á. Salichs Spain
Séverin Lemaignan United Kingdom
David Vernon Ireland
Daisuke Sakamoto relative to Naoyuki Kubota Japan Naoyuki Kubota's profile →
Citations per field
00.5×1.5×2.2×
Naoyuki Kubota · 1×
Citations per year

Countries citing papers authored by Daisuke Sakamoto

Since Specialization
Citations

This map shows the geographic impact of Daisuke Sakamoto's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daisuke Sakamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daisuke Sakamoto more than expected).

Fields of papers citing papers by Daisuke Sakamoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daisuke Sakamoto. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daisuke Sakamoto. The network helps show where Daisuke Sakamoto may publish in the future.

Co-authors

The 25 scholars most cited alongside Daisuke Sakamoto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daisuke Sakamoto Line = papers co-authored together Daisuke Sakamoto links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 168 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017188
2 2007175
3 2013139
4 2007115
5 201383
6 201082
7 201580
8 201879
9 200879
10 200978
11 201176
12 200673
13 201057
14 201253
15 201750
16 201448
17 201546
18 201043
19 200942
20 200942

About Daisuke Sakamoto

Daisuke Sakamoto is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Plant Science, Social Psychology and Control and Systems Engineering, having authored 168 papers that have together received 2.8k indexed citations. Recurring topics across this work include Interactive and Immersive Displays (37 papers), Plant Physiology and Cultivation Studies (30 papers), Social Robot Interaction and HRI (26 papers), Horticultural and Viticultural Research (19 papers), Tactile and Sensory Interactions (18 papers), Robotics and Automated Systems (15 papers), Gaze Tracking and Assistive Technology (14 papers) and Plant Reproductive Biology (14 papers). The work is most often cited by research in Human-Computer Interaction (798 citations), Social Psychology (858 citations), Computer Vision and Pattern Recognition (629 citations), Cognitive Neuroscience (369 citations) and Control and Systems Engineering (435 citations). Daisuke Sakamoto has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Takeo Igarashi, Hiroshi Ishiguro, Tetsuo Ono, Takayuki Kanda, Takaya Moriguchi, Masahiko İnami, Akiko Ito, Norihiro Hagita, Yuta Sugiura and Chia-Ming Chang. Their work appears in journals such as The Horticulture Journal, Tree Physiology, Scientia Horticulturae, International Journal of Social Robotics and ESC Heart Failure.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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